We provide world-class IT services for all your data and analytics needs in order to:
01
Reduce the cost of data handling at all levels.
02
Provide you with user-friendly tools for flexible reporting and quick analysis.
03
Build a firm foundation for data-driven business growth.
This case study
Problem
A Heavy Machinery dealer's top-level management was unhappy with the work done by their data analysis team.
They were especially concerned with the time taken to collect, analyze and visualize data upon request.
Sometimes, the analytical results were not provided on time, and the final decision had already been made.
When management found out that 3 full-time employees were engaged in updating existing reports manually, they decided it was time to take action.
Solution
1
We identified all existing reports and corresponding data sources, as well as provided comprehensive descriptions in the data catalogue.
2
We instantiated a cloud Data Lake based on Microsoft Azure cloud infrastructure.
3
Ingestion processes were configured for every single data source according to respective data types and business requirements.
4
Data from every source is now updated at lighting speed using Azure Synapse Pipelines, and stored in SQL-like storage. All data is ready to be evaluated by Power BI, both for reporting and analytics needs.
5
Specific data sets are generated, and all reports are transferred to Power BI with regular updates every morning, delivered via email.
Results
Now, analysts don't need to embark on a time-consuming mission every time a new report is needed. Instead, all they have to do is pick necessary data bits from the catalogue.
They can instantly connect to data gathered from 40+ business applications and use this data within minutes.
All new and existing reports are effortlessly updated by their data team.
Business Value
The average time for fulfilling any analytical request has dropped from 5 days to 4 hours. Decision-making speed has reached the next level.
The company began saving $ 360,000 on a yearly basis on manual data operations.
Growth-inhibiting data architecture has been replaced by a new, expandable system.
More details
Check out our CEO's article with more details on this implementation:
Our client β a major food tech company β has been using Excel spreadsheets for their data records for yearsβ¦ They were spending about 186! hours every month on updating all files and charts.
A major FMCG enterprise underwent a digital transformation and had various business projects across their departments β digital marketing, distribution management, procurement, human resources management, etc.
A mid-sized upstream Oil & Gas company, for decades, has been using conventional ways to forecast their reservoir's performance. Now they gather enough data to start using machine-learning algorithms.